Application of a 3D Bioprinted Hepatocellular Carcinoma Cell Model in Antitumor Drug Research

Lejia Sun, Huayu Yang, Yanan Wang, Xinyu Zhang, Bao Jin, Feihu Xie, Yukai Jin, Yuan Pang, Haitao Zhao, Xin Lu, Xinting Sang, Hongbing Zhang, Feng Lin, Wei Sun, Pengyu Huang, Yilei Mao, Lejia Sun, Huayu Yang, Yanan Wang, Xinyu Zhang, Bao Jin, Feihu Xie, Yukai Jin, Yuan Pang, Haitao Zhao, Xin Lu, Xinting Sang, Hongbing Zhang, Feng Lin, Wei Sun, Pengyu Huang, Yilei Mao

Abstract

The existing in vitro models for antitumor drug screening have great limitations. Many compounds that inhibit 2D cultured cells do not exhibit the same pharmacological effects in vivo, thereby wasting human and material resources as well as time during drug development. Therefore, developing new models is critical. The 3D bioprinting technology has greater advantages in constructing human tissue compared with sandwich culture and organoid construction. Here, we used 3D bioprinting technology to construct a 3D model with HepG2 cells (3DP-HepG2). The biological activities of the model were evaluated by immunofluorescence, real-time quantitative PCR, and transcriptome sequencing. Compared with the traditional 2D cultured tumor cells (2D-HepG2), 3DP-HepG2 showed significantly improved expression of tumor-related genes, including ALB, AFP, CD133, IL-8, EpCAM, CD24, and β-TGF genes. Transcriptome sequencing analysis revealed large differences in gene expression between 3DP-HepG2 and 2D-HepG2, especially genes related to hepatocyte function and tumor. We also compared the effects of antitumor drugs in 3DP-HepG2 and 2D-HepG2, and found that the large differences in drug resistance genes between the models may cause differences in the drugs' pharmacodynamics.

Keywords: 3D bio-printing; HCC model; anti-tumor drug development; drug screening; liver.

Copyright © 2020 Sun, Yang, Wang, Zhang, Jin, Xie, Jin, Pang, Zhao, Lu, Sang, Zhang, Lin, Sun, Huang and Mao.

Figures

Figure 1
Figure 1
Construction of the 3D bioprinted liver cancer cell model. (A) Schematic illustration of the 3D cell-printing process (left) and the image of the 3DP-HepG2 model directly after printing (right). Scale bar: 50 mm. (B) Top view of the 3DP-HepG2 model on days 0, 3, 5, 7, and 10 after printing. Scale bar: 1 mm. Bottom row shows magnified view of insets (square). (C) Cell diameter distribution in the 3DP-HepG2 model at 10 days after printing.
Figure 2
Figure 2
Cell survival and proliferation in the 3D bioprinted liver cancer cell model. (A) Cell viability at different times after printing. Representative live-dead staining images of 3DP-HepG2 structures at days 1, 3, 5, 7, and 10 after printing. Live and dead cells were labeled with calcein-AM (green) and PI (red), respectively. Scale bar: 300 μm. Histogram of cell viability at different times after printing (B) Proliferation rates of 3DP-HepG2 and 2D-HepG2 cells at different time points.
Figure 3
Figure 3
Liver-related protein expression in the 3D bioprinted liver cancer cell model. ALB, AFP, Ki67, and CYP3A4 protein expression in the 3DP-HepG2 model at 7 days after printing. Scale bar: 200 μm.
Figure 4
Figure 4
Tumor-related protein and mRNA expression in the 3D bioprinted liver cancer cell model. The mRNA expression of tumor-related genes, including (A) AFP, (B) TGF-β, (C) CD133, (D) EpCAM, (E) IL-8, and (F) CD24 in the 2D-HepG2 and 3DP-HepG2 models at 5, 10, and 15 days after 3D printing.
Figure 5
Figure 5
Transcriptional profiling characterization of 3D printed liver cancer cell model. (A) Heatmap of DEGs between the 3DP-HepG2 and 2D-HepG2 models. Rows represent genes, and columns represent samples. (B) Volcano plot showing 617 DEGs, including 235 significantly upregulated DEGs (red spots) and 382 significantly downregulated DEGs (green spots). KEGG pathway enrichment bubble chart of (C) significantly upregulated genes and (D) downregulated genes. The x–axis represents fold of enrichment and the y–axis represents KEGG–enriched terms. The size of the dot represents the number of genes under a specific term. The color of the dots represents adjustment. (E) The expression of liver cancer-specific genes in the 3DP-HepG2 and 2D-HepG2 models. The heatmap shows the expression of hepatocyte-related genes and tumor-related genes in the models. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.
Figure 6
Figure 6
Characteristics of drug metabolism in the 3D bioprinted liver cancer cell model. Dose-effect curves of cisplatin (A), sorafenib (B), and regorafenib (C) in the 3DP-HepG2 and 2D-HepG2 models after 72 h of treatment. The mRNA expression of drug resistance genes in the 2D-HepG2 and 3DP-HepG2 models at 5, 10, and 15 days after 3D printing. (D) MRP1, (E) BCRP, (F) ACBC1, (G) MDR-1, (H) MRP2, and (I) EGFR mRNAs.

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